Thesis (Ph. D.)--Oregon State University, 2006. / Printout. Includes bibliographical references (leaves 97-105). Also available on the World Wide Web.

Thesis (M.E.)--University of Canterbury, 2005. / Typescript (photocopy). Includes bibliographical references (p. [109]-116). Also available via the World Wide Web.

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2007. / Includes bibliographical references (leaves 73-77). Also available in electronic version.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

Thesis (M.S.)--University of Texas at Dallas, 2006. / Includes vita. Includes bibliographical references (leaves73 -75 )

Spatial Modulation (SM) is a spatial multiplexing technique designed for MIMO systems where only one transmit antenna is used at each time. It is considered to be an attractive choice for future wireless communication systems as it reduces Inter Channel Interference (ICI) while maintaining high energy efficiency. It can achieve this goal by mapping block of data bits into constellation points in the spatial and signal domain. Combining this innovative method with multiple access techniques could improve the system performance and enhance the data rate. In Code Division Multiple Access (CDMA) method employing parity bit permutation spreading, the bit error rate (BER) performance could be improved by using the parity bits to select the spreading sequence to use at each signalling interval. In this thesis, a new system model based on SM and CDMA employing parity bit permutation spreading is proposed and investigated. The proposed system takes advantage of the benefits of both techniques. In this system, in addition to use the parity bits to select the spreading sequences, same concept is used to select the combination of antennas to activate at each time instant. By doing so, a reduction of power consumption, Inter-Channel and Inter Symbol Interference effect can be achieved while keeping a certain diversity order compared to SM. Multiuser scenario is also discussed in order to investigate the multiple access interference (MAI) effects in synchronous transmission. In such case, the receiver estimates the desired user's information by considering the other users' signal as additional noise. Simulation results of the proposed MIMO-CDMA system employing permutation spreading show, for single user and multiuser, a significant improvement of the BER performance in low signal to noise ratio (SNR) when SM is implemented.

Massive MIMO is an emerging technology for future wireless systems that has received much attention from both academia and industry recently. The most prominent feature of Massive MIMO is that the base station is equiped with a large number of antennas. It is therefore important to create scalable architectures to enable simple deployment in different configurations. In this thesis, a distributed architecture for performing the baseband processing in a massive OFDM MU-MIMO system is proposed and analyzed. The proposed architecture is based on connecting several identical nodes in a K-ary tree. It is shown that, depending on the chosen algorithms, all or most computations can be performed in a distrbuted manner. Also, the computational load of each node does not depend on the number of nodes in the tree (except for some timing issues) which implies simple scalability of the system. It is shown that it should be enough that each node contains one or two complex multipliers and a few complex adders running at a couple of hundres MHz to support specifications similar to LTE. Additionally the nodes must communicate with each other over links with data rates in the order of some Gbps. Finally, a VHDL implementation of the system is proposed. The implementation is parameterized such that a system can be generated from a given specification.

With the introduction of 4G LTE, multiple new technologies were introduced. MIMO is one of the important technologies introduced with fourth generation. The main MIMO modes used in LTE are open loop and closed loop spatial multiplexing modes. This thesis develops an algorithm to calculate the threshold values of UE speed and SNR that is required to implement a switching algorithm which can switch between different MIMO modes for a UE based on the speed and channel conditions (CSI). Specifically, this thesis provides the values of UE speed and SNR at which we can get better results by switching between open loop and closed loop MIMO modes and then be scheduled in sub-channels accordingly. Thus, the results can be used effectively to get better channel capacity with less ISI. The main objectives of this thesis are: to determine the type of MIMO mode suitable for a UE with certain speed, to determine the effects of SNR on selection of MIMO modes, and to design and implement a scheduling algorithm to enhance channel capacity.

Massive MIMO has been recognized as a key technology for 5G systems due to its high spectral efficiency. The capacity and optimal signaling for a MIMO channel under the total power constraint (TPC) are well-known and can be obtained by the water-filling (WF) procedure. However, much less is known about optimal signaling under the per-antenna power constraint constraint (PAC) or under the joint power constraints (TPC+PAC). In this thesis, we consider a massive MIMO Gaussian channel under favorable propagation (FP) and obtain the optimal transmit covariance under the joint constraints. The effect of the joint constraints on the optimal power allocation (OPA) is shown. While it has some similarities to the standard WF, it also has number of notable differences. The numbers of active streams and active PACs are obtained, and a closed-form expression for the optimal dual variable is given. A capped water-filling interpretation of the OPA is given, which is similar to the standard WF, where a container has both floor and ceiling profiles. An iterative water-filling algorithm is proposed to find the OPA under the joint constraints, and its convergence to the OPA is proven. The robustness of optimal signaling under FP is demonstrated in which it becomes nearly optimal for a nearly favorable propagation channel. An upper bound of the sub-optimality gap is given which characterizes nearly (or eps)-favorable propagation. This upper bound quantifies how close the channel is to the FP. A bisection algorithm is developed to numerically compute the optimal dual variable. Newton-barrier and Monte-Carlo algorithms are developed to find the optimal signaling under the joint constraints for an arbitrary channel, not necessarily for a favorable propagation channel. When the diagonal entries of the channel Gram matrix are fixed, it is shown that a favorable propagation channel is not necessarily the best among all possible propagation scenarios capacity-wise. We further show that the main theorems in [1] on favorable propagation are not correct in general. To make their conclusions valid, some modifications as well as additional assumptions are needed, which are given here.

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